Linking To And Excerpting From Endotext’s “Assessing Insulin Sensitivity and Resistance in Humans”

Posted on May 14, 2026 by Tom Wade MD

Today, I review, link to, and excerpt from Endotext‘s* “Assessing Insulin Sensitivity and Resistance in Humans”. Last Update: October 16, 2024.

*Endotext is a Comprehensive FREE Online Endocrinology Book.

All that follows is from the above resource.

ABSTRACT

In this chapter we discuss a representative variety of methods currently available for estimating insulin sensitivity/resistance. These range from complex, time consuming, labor-intensive, invasive procedures to simple tests involving a single fasting blood sample. It is important to understand the physiological concepts informing each method so that relative merits and limitations of particular approaches are appropriately matched with proposed applications and data is interpreted correctly. The glucose clamp method is the reference standard for direct measurement of insulin sensitivity. Regarding simple surrogates, QUICKI and Log (HOMA) are among the best and most extensively validated. Dynamic tests are useful if information about both insulin secretion and insulin action are needed. For complete coverage of all related areas of Endocrinology, please visit our on-line FREE web-text, WWW.ENDOTEXT.ORG.

INTRODUCTION

Insulin resistance plays a major pathophysiological role in type 2 diabetes and is tightly associated with major public health problems including obesity, hypertension, coronary artery disease, dyslipidemias, and a cluster of metabolic and cardiovascular abnormalities that define the metabolic syndrome (, , ).

A global epidemic of obesity is driving the increased incidence and prevalence of type 2 diabetes and its cardiovascular complications (). Insulin resistance is commonly associated with visceral adiposity, glucose intolerance, hypertension, dyslipidemia, hypercoagulable state, endothelial dysfunction, and/or elevated markers of inflammation. Therefore, the presence of these clinical abnormalities is usually characteristic of an insulin resistant state. In addition to clinical manifestations of the “Insulin Resistance Syndrome,” insulin resistance predisposes to accelerated cardiovascular disease (CVD). Therefore, it is of great importance to develop tools for quantifying insulin sensitivity/resistance in humans that may be used to appropriately investigate the epidemiology, pathophysiological mechanisms, outcomes of therapeutic interventions, and clinical course of patients with insulin resistance (). In this chapter, we will discuss some currently used methods for assessing insulin sensitivity, their applications, merits, and limitations.

SIMPLE SURROGATE INDEXES FOR INSULIN SENSITIVITY/RESISTANCE

Surrogates Derived from Fasting Steady-state Conditions
PROCEDURE

After an overnight fast, a single blood sample is taken for determination of blood glucose and plasma insulin. In healthy humans, the fasting condition represents a basal steady-state where glucose is homeostatically maintained in the normal range such that insulin levels are not significantly changing and HGP is constant. That is, basal insulin secretion by pancreatic β cells determines a relatively constant level of insulinemia that will be lower or higher in accordance with insulin sensitivity/resistance such that HGP matches whole body glucose disposal under fasting conditions. Surrogate indexes based on fasting glucose and insulin concentrations reflect primarily hepatic insulin sensitivity/resistance. However, under most conditions, hepatic and skeletal muscle insulin sensitivity/resistance are proportional to each other. In the diabetic state with fasting hyperglycemia, fasting insulin levels are inappropriately low and insufficient to maintain euglycemia. Therefore, definitions of the more useful surrogate indexes take these considerations into account. Due to lack of a standardized insulin assay, it is not possible to use surrogate indexes to define universal cutoff points for insulin resistance.

ADVANTAGES AND LIMITATIONS
Simple surrogate indexes of insulin sensitivity/resistance are inexpensive quantitative tools that can be easily applied in almost every setting including epidemiological studies, large clinical trials, clinical research investigations, and clinical practice. If a direct measure of insulin sensitivity is not required, not feasible to obtain, or if insulin sensitivity is of secondary interest, it may be appropriate to use a surrogate index. The relative merits and limitations of individual surrogate indexes are discussed below.

The Homeostasis Model Assessment (HOMA)

HOMA, developed in 1985, is a model of interactions between glucose and insulin dynamics that is then used to predict fasting steady-state glucose and insulin concentrations for a wide range of possible combinations of insulin resistance and β-cell function (). The model assumes a feedback loop between the liver and β-cell (, , ); glucose concentrations are regulated by insulin- dependent HGP while insulin levels depend on the pancreatic β-cell response to glucose concentrations. Thus, deficient β-cell function reflects a diminished response to glucose-stimulated insulin secretion. Likewise, insulin resistance is reflected by diminished suppressive effect of insulin on HGP. HOMA model describes this glucose-insulin homeostasis by a set of empirically derived non-linear equations. The model predicts fasting steady- state levels of plasma glucose and insulin for any given combination of pancreatic β-cell function and insulin sensitivity. Computer simulations have been used to generate a grid from which mathematical transformations of fasting glucose and insulin β-cell function (HOMA %B) from steady-state conditions. An important caveat for HOMA is that it imputes dynamic β-cell function (i.e., glucose-stimulated insulin secretion) from fasting steady- state data. In the absence of dynamic data, it is difficult, if not impossible, to determine the true dynamic function of β-cell insulin secretion.

In practical terms, most studies using HOMA employ an approximation described by a simple equation to determine a surrogate index of insulin resistance. This is defined by the product of the fasting glucose and fasting insulin divided by a constant. Thus, HOMA-IR = fasting insulin (μU/ml) × fasting glucose (mmol/l) / 22.5. The constant is a normalizing factor, the product of fasting plasma insulin of 5 µU/mL and plasma glucose of 4.5 mmol/L obtained from an “ideal” and “normal” individual. Therefore, for an individual with normal insulin sensitivity, HOMA-IR = 1. It is important to note that over wide ranges of insulin sensitivity/resistance Log (HOMA-IR), (which normalizes the skewed distribution of fasting insulin values) determines a much stronger linear correlation with glucose clamp estimates of insulin sensitivity (). HOMA or Log (HOMA) is extensively used in large epidemiological studies, prospective clinical trials, and clinical research studies (, , ). In research settings where assessing insulin sensitivity/resistance is of secondary interest or feasibility issues preclude the use of direct measures by glucose clamp, it may be appropriate to use Log (HOMA-IR). However, as discussed below, other surrogate indexes have certain advantages over HOMA or Log (HOMA) in some circumstances.

Quantitative Insulin Sensitivity Check Index (QUICKI)

QUICKI is an empirically-derived mathematical transformation of fasting blood glucose and plasma insulin concentrations that provides a reliable, reproducible, and accurate index of insulin sensitivity with excellent positive predictive power (, ,, , ). Since fasting insulin levels have a non-normal skewed distribution, log transformation improves its linear correlation with SIclamp. However, as with 1/(fasting insulin) and the G/I ratio, this correlation is not maintained in diabetic subjects with fasting hyperglycemia and impaired β-cell function that is insufficient to maintain euglycemia. To accommodate these clinically important circumstances where fasting glucose is inappropriately high and insulin is inappropriately low, addition of log (fasting glucose) to log (fasting insulin) provides a reasonable correction such that the linear correlation with SIClamp is maintained in both diabetic and non-diabetic subjects. The reciprocal of this sum results in further transformation of the data generating an insulin sensitivity index that has a positive correlation with SIclamp. Thus, QUICKI = 1/Log (Fasting Insulin, µU/ml) + Log (Fasting Glucose, mg/dl). Over a wide range of insulin sensitivity/resistance, QUICKI has a substantially better linear correlation with SIclamp (r ≈ 0.8 – 0.9) than SI derived from the minimal model or HOMA-IR (, , ). Log (HOMA) is roughly comparable to QUICKI in this regard. Multiple independent studies find excellent linear correlations between QUICKI and glucose clamp estimates (either GIR or SIClamp) in healthy subjects, obesity, diabetes, hypertension, and many other insulin- resistant states (, , , , , , ). QUICKI is among the most thoroughly evaluated and validated surrogate index for insulin sensitivity. As a simple, useful, inexpensive, and minimally invasive surrogate for glucose clamp-derived measures of insulin sensitivity, QUICKI is appropriate and effective for use in large epidemiological or clinical research studies, to follow changes after therapeutic interventions, and for use in studies where evaluation of insulin sensitivity is not of primary interest.

Adipose Tissue Insulin Resistance Index (Adipo-IR)

Adipo-IR is a measure similar to HOMA-IR in that it is obtained from a fasting level of FFA and insulin (product of FFA and insulin levels). Recent studies have shown that Adipo-IR correlates well with the gold standard measure of adipose tissue insulin sensitivity derived from one-step hyperinsulinemic-euglycemic clamp technique using a palmitate tracer (). Age and physical fitness were however shown to affect the predictive values. Thus, Adipo-IR may be suitable for larger population studies, however the multistep pancreatic clamp technique is probably needed for mechanistic studies of adipose tissue insulin action.

 

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